library(dplyr)
library(tidyverse)
library(knitr)
library(plotly)
library(kableExtra)

1 Introduction

2 Domain knowledge

3 Data sources

3.1 World bank data

library(WDI)
 
#get datasets on emissions
datasets = WDIsearch("emissions")

# get Total greenhouse gas emissions (kt of CO2 equivalent)

ghg_emissions_wb = WDI(indicator='EN.ATM.GHGT.KT.CE')

# get all world data
ghg_emissions_wb_world = ghg_emissions_wb %>% 
  filter(country == "World")

# Show data sample 
ghg_emissions_wb_world %>% 
  top_n(10) %>% 
  kable() %>%
  kable_styling(bootstrap_options = c("striped", "hover"), full_width = F, font_size = 13) %>% 
  scroll_box(width = "100%", height = "400px")
iso2c country EN.ATM.GHGT.KT.CE year
1W World NA 2020
1W World NA 2019
1W World NA 2018
1W World NA 2017
1W World NA 2016
1W World NA 2015
1W World NA 2014
1W World NA 2013
1W World 53526303 2012
1W World 52790527 2011 
# plot world GHG emissions
ghg_emissions_wb_world %>% 
  plot_ly() %>% 
  add_trace(y = ~EN.ATM.GHGT.KT.CE, 
            x = ~year, 
            marker = list(color = "gray"),
            type = 'scatter',
            # type = "line",
            mode = 'lines+markers',
            orientation = "v") %>% 
  layout(title = "World GHG emissions (source: WorldBank)",
         yaxis = list(title = "GHG emissions"), 
         xaxis = list(title = "Years"))

3.2 World Resources Institute